Part 2 of our Machine Learning series is here! This time, we're going to cover the libraries required for you to work with Machine Learning. We're going to have hands-on exercises to work with numpy, scipy, matplotlib, and pandas.

The three part Machine Learning series will consist of:

1. Introduction to Python Programming

2. Introduction to Python ML prerequisite libraries: numpy, scipy, matplotlib, and pandas

3. Beginner ML with Tensorflow

The events form a series yet remain independent in nature, so having attended part 1 is NOT a must. 

If you're interested, but you're not familiar with Python, you can check out a recording of our first event here: https://youtu.be/LXrl-kB6abM 

The libraries we will cover are crucial prerequisites to Machine Learning with Python. For more details: 

• Numpy: Numerical operations (Matrix operations, vector operations, parallelized scalar operations)
• Pandas: Input data pre-processing (Load data from CSV, XML, JSON, Text files, etc.)
• Matplotlib: Plotting data (Scatter plots, histograms, pie charts, etc.)
• Scipy: Has multiple packages useful for processing raw sensor data and doing interpolation

If it all sounds like technical jargon, no worries! That's what our event is for. 

Looking forward to seeing you there!